A graph-based approach to skin mole matching incorporating template-normalized coordinates

Mirzaalian, Hengameh; Hamarneh, Ghassan; Lee, Tim K.

doi:10.1109/cvpr.2009.5206725

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Cited by 14 publications

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Skin Lesion Correspondence Localization in Total Body Photography

Huang,

Tashayyod,

Kang

et al. 2023

Lecture Notes in Computer Science

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Skin Lesion Correspondence Localization in Total Body Photography

Huang,

Tashayyod,

Kang

et al. 2023

Lecture Notes in Computer Science

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Automated Detection of New or Evolving Melanocytic Lesions Using a 3D Body Model

Bogo

Romero

Peserico

et al. 2014

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014

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Abstract. Detection of new or rapidly evolving melanocytic lesions is crucial for early diagnosis and treatment of melanoma. We propose a fully automated pre-screening system for detecting new lesions or changes in existing ones, on the order of 2 − 3mm, over almost the entire body surface. Our solution is based on a multi-camera 3D stereo system. The system captures 3D textured scans of a subject at different times and then brings these scans into correspondence by aligning them with a learned, parametric, non-rigid 3D body model. This means that captured skin textures are in accurate alignment across scans, facilitating the detection of new or changing lesions. The integration of lesion segmentation with a deformable 3D body model is a key contribution that makes our approach robust to changes in illumination and subject pose.

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